PL: fix style regressions

Author: Shotgunosine

nitransforms/surface.py

@@ -18,9 +18,6 @@
 from nitransforms.base import (
     SurfaceMesh
 )
-import nibabel as nb
-from scipy.spatial import KDTree
-from scipy.spatial.distance import cdist
 
 
 class SurfaceTransformBase():
@@ -231,12 +228,11 @@ def __init__(self, reference, moving, interpolation_method='barycentric', mat=No
         # transform
         if mat is None:
             self.__calculate_mat()
-            r_tree = KDTree(self.reference._coords)
             m_tree = KDTree(self.moving._coords)
-            kmr_dists, kmr_closest = m_tree.query(self.reference._coords, k=10)
+            _, kmr_closest = m_tree.query(self.reference._coords, k=10)
 
             # invert the triangles to generate a lookup table from vertices to triangle index
-            tri_lut = dict()
+            tri_lut = {}
             for i, idxs in enumerate(self.moving._triangles):
                 for x in idxs:
                     if not x in tri_lut:
@@ -247,7 +243,7 @@ def __init__(self, reference, moving, interpolation_method='barycentric', mat=No
             # calculate the barycentric interpolation weights
             bc_weights = []
             enclosing = []
-            for sidx, (point, kmrv) in enumerate(zip(self.reference._coords, kmr_closest)):
+            for point, kmrv in zip(self.reference._coords, kmr_closest):
                 close_tris = _find_close_tris(kmrv, tri_lut, self.moving)
                 ww, ee = _find_weights(point, close_tris, m_tree)
                 bc_weights.append(ww)

nitransforms/tests/test_surface.py

@@ -1,4 +1,3 @@
-import os
 import tempfile
 
 import numpy as np
@@ -12,10 +11,6 @@
     SurfaceResampler
 )
 
-from nitransforms.base import SurfaceMesh
-from nitransforms.surface import SurfaceCoordinateTransform, SurfaceResampler
-
-
 # def test_surface_transform_npz():
 #     mat = sparse.random(10, 10, density=0.5)
 #     xfm = SurfaceCoordinateTransform(mat)
@@ -209,4 +204,3 @@ def test_SurfaceResampler(testdata_path, tmpdir):
     assert resampling3 == resampling
     resampled_thickness3 = resampling3.apply(subj_thickness.agg_data(), normalize='element')
     assert np.all(resampled_thickness3 == resampled_thickness)
-